Bespoke Applied Artificial Intelligence and LLM Engineering with Python Training Course
Course Overview
This practical training programme is tailored for data engineering professionals aiming to develop tangible skills in artificial intelligence, Python programming, and large language models. The curriculum centres on real-world applications, addressing model utilisation, prompt engineering, and the creation of AI-driven solutions. Participants will engage in a series of progressive exercises that transition from fundamental concepts to the development of deployable AI workflows.
Training Format
• In-person classroom-based training
• Instructor-led sessions featuring guided practice
• Interactive discussions and real-world case studies
• Daily hands-on exercises
Course Objectives
• Grasp core AI and machine learning concepts pertinent to contemporary applications
• Enhance Python proficiency for AI development and data workflows
• Comprehend the mechanics of large language models and their effective utilisation
• Design and optimise prompts for consistent and reliable outputs
• Construct end-to-end AI solutions utilising APIs and frameworks
• Integrate AI capabilities into data engineering pipelines
This course is available as onsite live training in Botswana or online live training.
Course Outline
Course Outline Training Proposal
Day 1 - Introduction to AI and Python for Data Workflows
• Overview of the artificial intelligence and machine learning landscape
• The role of AI in modern data engineering
• Refresher on Python fundamentals for AI applications
• Data manipulation using pandas and NumPy
• Introduction to APIs and JSON data handling
• Mini exercise: loading and transforming datasets
Day 2 - Machine Learning Foundations for Practitioners
• Concepts of supervised and unsupervised learning
• Feature engineering and data preparation techniques
• Fundamentals of model training using scikit-learn
• Model evaluation and performance metrics
• Introduction to model deployment concepts
• Hands-on session: building a simple predictive model
Day 3 - Introduction to LLMs and Prompt Engineering
• Understanding large language models and their underlying mechanisms
• Tokenization, context windows, and inherent limitations
• Principles and techniques for prompt design
• Zero-shot and few-shot prompting strategies
• Prompt evaluation and iteration strategies
• Hands-on prompt engineering exercises
Day 4 - Building AI Applications with LLMs
• Utilising LLM APIs in Python
• Structured outputs and function calling concepts
• Developing chat-based and task-oriented applications
• Introduction to retrieval augmented generation
• Connecting LLMs with external data sources
• Mini project: constructing a basic AI assistant
Day 5 - Productionizing AI Solutions
• Designing scalable AI workflows
• Integrating AI into data pipelines
• Monitoring and improving model performance
• Cost optimization and API usage strategies
• Security and responsible AI considerations
• Final project: building an end-to-end AI solution
Need help picking the right course?
southafrica@nobleprog.co.za or +27 (0)10 005 5793
Bespoke Applied Artificial Intelligence and LLM Engineering with Python Training Course - Enquiry
Testimonials (2)
The trainer was very available to answer all te kind of question I did
Caterina - Stamtech
Course - Developing APIs with Python and FastAPI
Trainer develops training based on participant's pace
Farris Chua
Course - Data Analysis in Python using Pandas and Numpy
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